Papers by Keyang Zhong

1 papers
Collaborative Multi-Agent Scripts Generation for Enhancing Imperfect-Information Reasoning in Murder Mystery Games (2026.findings-acl)

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Challenge: Vision-language models have shown impressive capabilities in perceptual tasks . however, they degrade in complex multi-hop reasoning under multi-player game settings .
Approach: They propose a multi-agent framework for evaluating and synthesizing role-driven game scripts . they use curated and synthetic datasets to model uncertainty and deception .
Outcome: The proposed model significantly boosts the performance of VLMs in narrative reasoning and hidden fact extraction under uncertain, adversarial, and socially complex conditions.

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